Papers
Who Should Predict? Exact Algorithms For Learning to Defer to Humans
Hussein Mozannar, Hunter Lang, Dennis Wei et al.
A Bandit Model for Human-Machine Decision Making with Private Information and Opacity
Sebastian Bordt, Ulrike Von Luxburg
A Bayesian Approach for Stochastic Continuum-armed Bandit with Long-term Constraints
Zai Shi, Atilla Eryilmaz
A Bayesian Model for Online Activity Sample Sizes
Thomas S. Richardson, Yu Liu, James Mcqueen et al.
A cautionary tale on fitting decision trees to data from additive models: generalization lower bounds
Yan Shuo Tan, Abhineet Agarwal, Bin Yu
Acceleration in Distributed Optimization under Similarity
Ye Tian, Gesualdo Scutari, Tianyu Cao et al.
Accurate Shapley Values for explaining tree-based models
Salim I. Amoukou, Tangi Salaün, Nicolas Brunel
A Class of Geometric Structures in Transfer Learning: Minimax Bounds and Optimality
Xuhui Zhang, Jose Blanchet, Soumyadip Ghosh et al.
A Complete Characterisation of ReLU-Invariant Distributions
Jan Macdonald, Stephan Wäldchen
A Contraction Theory Approach to Optimization Algorithms from Acceleration Flows
Pedro Cisneros-Velarde, Francesco Bullo
A Cramér Distance perspective on Quantile Regression based Distributional Reinforcement Learning
Alix Lheritier, Nicolas Bondoux
Ada-BKB: Scalable Gaussian Process Optimization on Continuous Domains by Adaptive Discretization
Marco Rando, Luigi Carratino, Silvia Villa et al.
AdaBlock: SGD with Practical Block Diagonal Matrix Adaptation for Deep Learning
Jihun Yun, Aurelie Lozano, Eunho Yang
Adaptation of the Independent Metropolis-Hastings Sampler with Normalizing Flow Proposals
James Brofos, Marylou Gabrie, Marcus A. Brubaker et al.
Adaptive A/B Test on Networks with Cluster Structures
Yang Liu, Yifan Zhou, Ping Li et al.
Adaptive Gaussian Processes on Graphs via Spectral Graph Wavelets
Felix Opolka, Yin-Cong Zhi, Pietro Lió et al.
Adaptive Importance Sampling meets Mirror Descent : a Bias-variance Tradeoff
Anna Korba, François Portier
Adaptive Multi-Goal Exploration
Jean Tarbouriech, Omar Darwiche Domingues, Pierre Menard et al.
Adaptive Private-K-Selection with Adaptive K and Application to Multi-label PATE
Yuqing Zhu, Yu-Xiang Wang
Adaptive Sampling for Heterogeneous Rank Aggregation from Noisy Pairwise Comparisons
Yue Wu, Tao Jin, Hao Lou et al.
A Dimensionality Reduction Method for Finding Least Favorable Priors with a Focus on Bregman Divergence
Alex R. Dytso, Mario Goldenbaum, H. Vincent Poor et al.
A Dual Approach to Constrained Markov Decision Processes with Entropy Regularization
Donghao Ying, Yuhao Ding, Javad Lavaei
Adversarially Robust Kernel Smoothing
Jia-Jie Zhu, Christina Kouridi, Yassine Nemmour et al.
Adversarial Tracking Control via Strongly Adaptive Online Learning with Memory
Zhiyu Zhang, Ashok Cutkosky, Ioannis Paschalidis